Predicting life expectancy

Predicting life expectancy#

# TBA: header image

It is no secret that life expectancy has been increasing rapidly over the past couple of decades. A crucial indicator of a nation’s health and well-being can be traced back to its life expectancy statistic. This statistic is influenced by a multitude of factors, such as: economic stability, healthcare quality lifestyle, education, environmental conditions and many more. The question begs however, which of these factors contribute the most to a nation’s life expectancy? One might argue that only education plays a role, because all other factors are dependent on it. Another person might argue that not all of these factors are dependent on a nation’s level of education, thus its impact might not be as significant as one expects. This project aims to put these two perspectives to the test, by analyzing several key factors contributing to a nation’s life expectancy.

Several datasets about factors related to life expectancy are used in this project. Using sophisticated modeling techniques and visualization, relevant data of these factors are compared to eachother. The objective is to provide both perspectives with sufficient arguments to defend their statement. The insights provided in this project may help determine whether education is the only factor contributing to life expectancy.

It is important to note the pace at which life expectancy has skyrocketed over the past decades. The extraordinary rise is attributed to a wide range of advances in human development. At the start of the nineteenth century, no region had a life expectancy higher than 40 years. Nowadays, multiple countries are close to hitting 80 years, according to ourworldindata. This rapid increase in life expectancy can be visualized using a box plot.

%run life_expectancy_boxplot.ipynb

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Name: count, dtype: int64

Only education and GDP have an impact on life expectancy#

As seen in the dataset, it’s very common for countries with a good education to also have a high life expectancy. To make it more clear, the data can be visualized in this Bivariate Choropleth:

In this image, the left side of the legend is the education level, and the right side is the life expectancy. As shown, almost all countries with good education quality also have a high life expectancy. The reasoning behind this might be that people with better education tend to choose for a healthier way of life. It can also be visualized in the following way. This plot shows the rate in which people finish primary and secondary school, compared to the life expectancy of said person. This graph makes clear that people with better education tend to have a higher life expectancy. A reason for this increase in life expectancy comes from the fact that people with a better education make better choices. (Raghupathi & Raghupathi, 2020b)

Education level#

Assuming education is the only factor that predicts life expectancy in a country, a closer assessment is needed to determine which sector should be invested in.

Second plot#

GDP Argument (Second argument)#

We can also argue that a society with a good education will produce an increasing GDP. Research at the university of Munich has shown that people with a better education are able to achieve jobs with more complex skill sets, resulting in a higher paying job. If people in a society are able to keep higher paying jobs, the GDP from the country of origin will increase. This in turn will influence the life expectancy of a country. Research originating from the University of Zagreb has shown that an increase in GDP of a country, also has a positive influence on the country’s life expectancy. This is confirmed when you convert the data into a Bivariate Chropleth or a scatter plot (with a regression). These charts show the GDP of a country and the country’s life expectancy. This means that the increase in education gives an increase in GDP which delivers an increase in life expectancy.

../_images/26a812fa259c814efdbec03faf24ef3c55d183a7c19e04ce190b17a72ea0d178.png

Life expectancy cannot be predicted by just education#

Even though A country investing in their education program results in an increase in life expectancy. There are more direct approaches to increasing a country’s life expectancy. One possible solution is investing in increasing the country’s vaccination rate. Diseases or viruses like Polio and Diphtheria can be fatal if not treated appropriately, in some cases (like for polio) there is no cure at all. Not treating these diseases results in a drastic decrease in life expectancy. So instead of investing in education to improve life expectancy, a country should invest in vaccines as this has a more direct effect. This can be seen in the plot where it shows an increase in vaccination rate for polio and Diphtheria corresponds with an increase in life expectancy. This is also found in the research by Jenifer Ehreth. Which concludes that improving the vaccination rate is a big factor in increasing a country’s life expectancy. https://www.sciencedirect.com/science/article/pii/S0264410X03003773

Unhealthy lifestyles#

The prevelance of unhealthy lifestyles in (developed) countries may also contribute to life expectancy.

Counter argument 2#

Another way to increase life expectancy is to invest in cleaner and safer drinking water. Unsafe drinking water is the cause of a lot of different diseases, all of which can cause a person to live a shorter life. It can be seen in the graph that an increase in the amount of people that drink from a safe water source correlates with an increase in life expectancy, this also supported by the following research paper, Angelakis et al. (2021b). This means that it should be useful for a country to invest in a clean water source before it starts to invest in different areas.

The impact of vaccination#

Another factor to consider is

Conclusion#

hier moet nog een conclusie komen

References#

Raghupathi, V., & Raghupathi, W. (2020). The influence of education on health: an empirical assessment of OECD countries for the period 1995–2015. Archives Of Public Health, 78(1). https://doi.org/10.1186/s13690-020-00402-5
Ehreth, J. (2003). The value of vaccination: a global perspective. Vaccine, 21(27–30), 4105–4117. https://doi.org/10.1016/s0264-410x(03)00377-3
Angelakis, A. N., Vuorinen, H. S., Nikolaidis, C., Juuti, P. S., Katko, T. S., Juuti, R. P., Zhang, J., & Samonis, G. (2021). Water Quality and Life Expectancy: Parallel Courses in Time. Water, 13(6), 752. https://doi.org/10.3390/w13060752